Josef Heinen - Getting more out of Matplotlib with GR Python is well established in software development departments of research and industry, not least because of the proliferation of libraries such as _SciPy_ and _Matplotlib_. However, when processing large amounts of data, in particular in combination with GUI toolkits (_Qt_) or three-dimensional visualizations (_OpenGL_), Python as an interpretative programming language seems to be reaching its limits. In particular, large amounts of data or the visualization of three- dimensional scenes may overwhelm the system. This presentation shows how visualization applications with special performance requirements can be designed on the basis of _Matplotlib_ and _GR_, a high-performance visualization library for Linux, OS X and Windows. The lecture focuses on the development of a new graphics backend for _Matplotlib_ based on the _GR_ framework. By combining the power of those libraries the responsiveness of animated visualization applications and their resulting frame rates can be improved significantly. This in turn allows the use of _Matplotlib_ in real- time environments, for example in the area of signal processing. Using concrete examples, the presentation will demonstrate the benefits of the [GR framework] as a companion module for _Matplotlib_, both in _Python_ and _Julia_. Based on selected applications, the suitability of the _GR framework_ will be highlighted especially in environments where time is critical. The system’s performance capabilities will be illustrated using demanding live applications. In addition, the special abilities of the _GR framework_ are emphasized in terms of interoperability with graphical user interfaces (_Qt/PySide_) and _OpenGL_, which opens up new possibilities for existing _Matplotlib_ applications.